Big Data, Machine Learning and Computer Bias

• Big Data is data sets that are so voluminous and complex that traditional data processing application software are inadequate to deal with them.
• Big Data is becoming increasingly easier and cheaper to obtain for several reasons:

  • The Internet 
  • The Internet of Things 
  • Storage Capacity
• The world’s technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s.
• Big data analytics describes the process of uncovering trends, patterns, and correlations in large amounts of raw data to help make data-informed decisions.
• Analysis of big data seeks to spot business trends, prevent diseases, combat crime, predict user behavior, and so on.
• Machine learning (ML) is a type of algorithm that automatically improves itself based on experience
• Reinforcement learning - The algorithm performs actions that will be rewarded the most. Often used by game-playing AI or navigational robots.
• Unsupervised machine learning - The algorithm finds patterns in unlabeled data by clustering and identifying similarities. Popular uses include recommendation systems and targeted advertising.
• Supervised machine learning - The algorithm analyzes labeled data and learns how to map input data to an output label. Often used for classification and prediction.